Is Your Bank Embracing the Leading Indicators of Credit Risk?

03/03/2017

by Mikkalya "Mikki" Murray
Senior VP & Managing Director, Credit Risk Management

"He shall fare well who confronts circumstances aright."  
-Plutarch


Basic Concept

A simple concept...to identify circumstances, i.e., “risk” aright, and be better for it, as Plutarch would have said, applying meaningful strategies relative to managing, measuring, monitoring and mitigating risk. In the context of community banking credit risk management, this segment of the banking industry continues to evolve relative to the use of indicative measurements of risk within credit portfolios. Credit Risk professionals have generally used lagging indicators such as Delinquency Ratio, Classified Asset Ratio, Non-Performing Ratio, Texas Ratio, and other historical metrics to measure the level of risk in credit portfolios. While these indicators remain useful tools in measuring the level of credit risk already embedded in loan portfolios, these ratios speak only to the current or historic level of risk. Best practice techniques suggest that it is better to include trend analysis and measures which are indicative of the additional level of risk that will become apparent in the future within a portfolio.

Throughout my credit risk management career, and during my time performing loan review, consulting and due diligence services for Ardmore Banking Advisors’ clients, I have employed and observed many early warning or leading indicators that can be used to assess not only the historic level of credit risk, but aid in predicting future levels of risk. By utilizing both lagging (historic) and leading (predictive) indicators in tandem, banks are better able to incrementally manage and assess any deterioration in its portfolio on an ongoing basis and prepare to manage changing levels of credit risk going forward. In my opinion, credit risk professionals who do not manage using both lagging and leading indicators miss the opportunity to use indicative tools, and therefore cannot “confront circumstances (risks) aright”, which is the most effective means of mitigating increased portfolio risks.

Community bank credit professionals have asked, “How do we incorporate indicative tools into our credit risk management process?” While specific techniques often depend on the composition of the loan portfolio and loan operating systems and tools that the bank may have to work with, here are a few examples of over-reliance on lagging indicators and what may be better indicative tools.

Example - Cash Flow / Debt Service Warning Signals:

Bank provides a working capital LOC. The bank tests DSC annually, and it has been adequate (lagging indicator), but the bank does not receive interim financial statements or informal borrowing base certificates. Bank does not check monthly or quarterly for line usage. Bank does not analyze or incorporate over-draft activity into a timely review of the borrower. At Ardmore, we have observed instances when there have been clear indicators of increasingly heavy reliance on an LOC (perhaps evergreen), occasional over-drafts, and no requirement for interim financials, no analysis of the asset conversion cycle, and / or no requirement to have detailed analysis performed when overdrafts occur.

Conclusion: While historic DSC has been adequate, risk is increasing (overdrafts, heavy line usage). Banks that create reports showing DDA activity combined with LOC O/S and line usage, AND require action / analysis when risk events occur, are better able to manage the risk (and possibly better able to advise the customer). Reports should also be elevated to senior / executive management to ensure that action is taken and obtain assistance from the most experienced credit minds in the bank.

Example – Approved Exceptions to Policy (ETP - DSC) and Future Risk Levels:  

Bank captures ETPs on all new approvals on a report and shares this data with senior / executive management and the BOD (when applicable), as well as the lender. At Ardmore, we have observed instances when there has been limited or no further analysis and of future performance of the population of loans with DSC ETPs. How might the bank use the DSC ETP data (lagging indicator) as a leading indicator to predict future risk?

Example: Select all approvals with DSC ETPs from 1Q2015 and track this population over a five-year period on a periodic basis (quarterly, semi-annually). Track this 1Q2015 ETP “vintage” along with DSC, any new credit admin exceptions (F/S or other reporting), O/D activity, and delinquency. Track all approvals without ETP for comparison on performance. Analyze the data periodically to assess any emerging risks within this vintage population and assess any correlation to between “1Q15 DSC ETP vintage” and future increases in credit risk. By performing this analysis on vintage populations, the bank can assess whether risks are emerging and whether there is a correlation (co-variance) with loans booked with ETPs. If assessments indicate a trend, for example: loans approved with DSC ETP <1X DSC and future O/Ds, reporting issues, or delinquency, then the Bank may take steps to more aggressively manage credits which exhibit these higher risk attribute (DSC <1X), and / or consider a more conservative policy relative the approving DSC <1X. Trend assessments of one vintage may or may not be extrapolated to another vintage

Example – Approved Exceptions to Policy (LTV ETP) and Future Risk Levels:

Bank captures LTV ETPs on all new approvals on a report and shares this data with senior / executive management and the BOD (when applicable), as well as the lender. How might the bank use the LTV ETP data (lagging) to be leading and predictive of future risk?

Example: Select all approvals with LTV ETPs from 1Q2015 and track this population over a five-year period on a periodic basis (quarterly, semi-annually). Track this 1Q2015 ETP vintage along with LTV, any new credit admin exceptions (F/S or other reporting), O/D activity, and delinquency. Analyze the data periodically to assess any emerging risks within this vintage population to assess any correlation between LTV ETP and future credit performance or loss. By performing this analysis on vintage populations the bank can assess whether risks are emerging and whether there is a correlation (co-variance) with loans booked with LTV ETPs. If assessments indicate a trend, for example: loans approved with LTV ETP >80% and future O/Ds, reporting issues, and delinquency, then the Bank may take steps to more aggressively manage credits which exhibit these higher risk attribute (LTV >80%), and / or consider a more conservative policy. Banks should also correlative LTV ETP to any loss experience; again the idea is to assess whether loans approved with LTV ETPs, on an indicative basis, lead to higher credit risk (while still performing, at time of default and / at time of loss).

Conclusion

A bank that does not look to assess trends using both historic data and trend analysis as part of its overall credit risk management process may be missing an important credit risk management step - embracing leading indicators and trend analysis to identify emerging risks and act proactively.

Ardmore Banking Advisors is available to consult with banks that are interested in incorporating more robust credit risk practices into their credit risk management plans. We are able to highlight the factors that matter most in determining credit risk, and, perhaps more importantly, identify factors that don’t correlate well, saving your bank time and resources. At Ardmore Banking Advisors, we encourage you to confront credit risks aright.

Mikki Murray is Senior VP and Managing Director at Ardmore Banking Advisors, where she has worked for five years. Before joining Ardmore, she was Chief Credit Officer for a $3B community bank, a past president of the Risk Management Association (RMA)'s Philadelphia chapter, past RMA National Board member and an RMA CRC.